bert-base-uncased-finetuned-QnA

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.0604

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	20	3.4894
No log	2.0	40	3.5654
No log	3.0	60	3.3185
No log	4.0	80	3.2859
No log	5.0	100	3.2947
No log	6.0	120	3.3998
No log	7.0	140	3.1642
No log	8.0	160	3.2653
No log	9.0	180	3.3427
No log	10.0	200	3.3549

Framework versions

• Transformers 4.9.1
• Pytorch 1.9.0+cu102
• Datasets 1.10.2
• Tokenizers 0.10.3